Methods for exact perturbation analysis

Miller, D and Morgan, Byron J. T. and Ridout, Martin S. and Carey, P.D. and Rothery, P. (2011) Methods for exact perturbation analysis. Methods in Ecology and Evolution, 2 (3). pp. 283-288. ISSN 2041-210X. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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1. The dominant eigenvalue of the population projection matrix provides the asymptotic growth rate of a population. Perturbation analysis examines how changes in vital rates and transitions affect this growth rate. The standard approach to evaluating the effect of a perturbation uses sensi- tivities and elasticities to provide a linear approximation. 2. A transfer function approach provides the exact relationship between growth rate and perturba- tion matrix. An alternative approach derives the exact solution directly by calculating the matrix characteristic equation in terms of the perturbation parameters and the asymptotic growth rate. This may be calculated numerically or by using symbolic algebra, and here we focus on the symbolic algebra approach. 3. The direct approach provides integrated sensitivities and plots of the exact relationship. The same method may be used for any perturbation structure, however complicated, including pertur- bations to vital rates that determine the elements of the population projection matrix. 4. The simplicity of the direct approach is illustrated through two examples, the killer whale and the lizard orchid. 5. Synthesis and applications. In this paper we describe three different methods for exact perturba- tion analysis. It is shown that each has its own merits, and the associated online computer code will encourage wider use of this analysis in the future.

Item Type: Article
Uncontrolled keywords: asymptotic growth rate, characteristic equation, elasticity, Maple, numerical method, population, projection matrix, sensitivity, symbolic algebra, transfer function
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Q Science > QH Natural history > QH541 Ecology
Divisions: Faculties > Sciences > School of Mathematics Statistics and Actuarial Science
Depositing User: Byron Morgan
Date Deposited: 17 Jan 2013 17:20 UTC
Last Modified: 02 Jun 2014 11:26 UTC
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